sabre: or how to compare two maps?

Creating or determination of regions is a useful way to describe the world. Regionalization does not only allow for a quicker understanding of spatial patterns but also can influence how regions are managed. Regions are created in various disciplines. We can delineate regions based on a single property (e.g. landform regions or climate regions) or several factors (e.g. ecoregions). There are also political regions divided by borders that are established through political or social agreements.

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Moving beyond pattern-based analysis: Additional applications of GeoPAT 2

This is the sixth and the last blog post in the series introducing GeoPAT 2 - a software for pattern-based spatial and temporal analysis. In the previous one we presented the pattern-based spatial segmentation - a method for creating regions of homogenous patterns. Here, we will mention other pattern-based methods and show some examples of how you can use pieces of GeoPAT 2 in your own workflow. Introduction GeoPAT 2 gives its users a lot of freedom, having a large number of possible workflows:

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Life (expectancy), animated

Global socio-economic data is easily accessible nowadays. Just type the indicator of interest and the name of the country in your preferred search engine and you can find its value, sometimes also an additional plot or a map. But what about when you want to go further and (for example): Want to compare many countries? Get data just for a specific year? See changes in time? Just want to create a very specific plot or a map?

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Making maps of the USA with R: alternative layout

Introduction Maps of United States often focus only on the contiguous 48 states. In many maps Alaska and Hawaii are simply not shown or are displayed at different geographic scales than the main map. This article shows how to create inset maps of the USA, building on a chapter in the in-development book Geocomputation with R that shows all its states and ensures relative sizes are preserved. It requires up-to-date versions of the following packages to be loaded:1

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Geocomputation with R - the intermission

Hello everybody! A lot of things have changed since the last blogpost about Geocomputation with R. In this post I’ll give an update of our progress and our plans for the next chapters. Third author Probably the most important change is having a third author - Jannes Muenchow. He is a GIScientist based at the University of Jena with a keen interest in spatial and geostatistical modeling, algorithm automation and geocomputation.

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Geocomputation with R - the beginnings

Just over one year ago, I met Robin in Poznan, Poland, who was teaching as part of the GEOCENTRUM project at the Adam Mickiewicz University. To our surprise, we found that we shared an idea of writing a book explaining how to use R for spatial data analysis. The timing worked well. Over the next few months, Robin finished Phase II of his project (the Propensity to Cycle Tool (PCT)) and I completed my PhD and moved to Cincinnati to work in Space Informatics Lab.

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